Experienced in writing code, building complex neural networks, and solving problems using transformer-based models (BERT, GPT3, Roberta). I have comprehensive knowledge of deep learning concepts and enjoy explaining them to non-technical audiences. I have experience in creating synthetic datasets, Data gathering, analyzing data and enhancing existing models. Finally, I'm passionate about reading the latest research papers on new emerging technologies in the field of Natural Language Processing.What Have I worked on?- Fine-tuning large language models for custom use cases using Mistral 7b, Llama2, FlanT5, and GPT-2.- Building RAG applications using Open Source LLM’s, Langchain and Weaviate Vector Database.- Synthetic dataset creation using LLM’s- Deployed models on AWS Sagemaker and EC2.- Prompt Engineering various LLM models.PROJECTS:- Worked on the AI (Prompt Engineering) for https://craftly.ai/- User Feedback Analysis, using RAG, LLMS(www.feedbacksync.ai)- AI Marketing tool using LLMS (www.sparky.ai)- Fine Tuning GPT Neo to Generate Quotes- Fine Tuning BERT model for Game Review Classification- Multilabel Classification of Public Sector Contracts- Emotion Recognition Through Tweets using Pretrained Embeddings and BERT- Scraping Hotel reviews using Selenium- Performing EDA on Cyberpunk 2077 (Steam Game)- Text Classification on Amazon Product Reviews- Auto Watering and Sun Seeking System- Report Generation using python- Assessment Dashboard for Analysis